MV
M.A.R.C.M. Verzijl
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1
Master thesis
(2020)
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M.A.R.C.M. Verzijl, B.P.F. Lelieveldt, J. Dijkstra, J.R. van der Vorst, F.M. Vos, S. Pintea
While millions of people world wide suffer from arterial diseases, such as peripheral arterial disease, there are a limited number of methods that can be used to diagnose and track these diseases which are also easy, quick and non-invasive.
This work focuses on what is needed to improve diagnosing and tracking of peripheral arterial disease (PAD) using visualisation techniques. Visualising the blood flow pulsation in the skin can be useful in cases of arterial diseases, as the diseases can influence the blood flow by obstructions and arterial stiffness. The main objective in the visualisation is to show the acceleration of the blood flow, as this is linked to the arterial stiffness.
The proposed algorithm for visualising the acceleration of the blood flow is comprised of multiple steps, including techniques such as motion reduction, Eulerian video magnification, remote photoplethysmography signal extraction and using the second derivative. The input of this algorithm are videos of the skin of patients, this makes this method easy and non-invasive.
Photoplethysmography (PPG) signals are present in videos of skin, but can not be seen with the naked eye. Using Eulerian video magnification the PPG signals are amplified for better processing and visibility. By combining groups of pixels into small patches, a decrease in processing time is achieved and it adds a filtering effect. The size of the patches controls the resolution of the visualisation. Movement from the camera or patient is detrimental when extracting the PPG signal from the video. To counteract the motion in the videos a motion reduction step, using optical flow, is applied. Using the Plane-orthogonal-to-skin (POS) algorithm, the signal extracted from videos is converted to a PPG signal. Calculating the second derivative of the PPG signal gives the acceleration of the signal. By splitting the acceleration signal into positive and negative numbers, the acceleration and deceleration of the blood flow is visualised.
Synthetic videos simulating the skin were generated in various levels of accuracy to aid the development of the algorithm and to conduct experiments. The levels range from a simple pulsating square to a moving PPG signal over a blood vessel like structure. In addition, real videos of patients were used.
The experiments show the feasibility of visualising the acceleration of the blood flow pulsation in the skin, but also highlights areas of improvements and future research. More fine-tuning of the algorithm is needed, in addition to acquiring more videos of patients with PAD before and after surgery in a controlled environment.
A working proof of concept of the algorithm is shown. It has the potential of being a novel method of diagnosing and tracking arterial diseases. ...
This work focuses on what is needed to improve diagnosing and tracking of peripheral arterial disease (PAD) using visualisation techniques. Visualising the blood flow pulsation in the skin can be useful in cases of arterial diseases, as the diseases can influence the blood flow by obstructions and arterial stiffness. The main objective in the visualisation is to show the acceleration of the blood flow, as this is linked to the arterial stiffness.
The proposed algorithm for visualising the acceleration of the blood flow is comprised of multiple steps, including techniques such as motion reduction, Eulerian video magnification, remote photoplethysmography signal extraction and using the second derivative. The input of this algorithm are videos of the skin of patients, this makes this method easy and non-invasive.
Photoplethysmography (PPG) signals are present in videos of skin, but can not be seen with the naked eye. Using Eulerian video magnification the PPG signals are amplified for better processing and visibility. By combining groups of pixels into small patches, a decrease in processing time is achieved and it adds a filtering effect. The size of the patches controls the resolution of the visualisation. Movement from the camera or patient is detrimental when extracting the PPG signal from the video. To counteract the motion in the videos a motion reduction step, using optical flow, is applied. Using the Plane-orthogonal-to-skin (POS) algorithm, the signal extracted from videos is converted to a PPG signal. Calculating the second derivative of the PPG signal gives the acceleration of the signal. By splitting the acceleration signal into positive and negative numbers, the acceleration and deceleration of the blood flow is visualised.
Synthetic videos simulating the skin were generated in various levels of accuracy to aid the development of the algorithm and to conduct experiments. The levels range from a simple pulsating square to a moving PPG signal over a blood vessel like structure. In addition, real videos of patients were used.
The experiments show the feasibility of visualising the acceleration of the blood flow pulsation in the skin, but also highlights areas of improvements and future research. More fine-tuning of the algorithm is needed, in addition to acquiring more videos of patients with PAD before and after surgery in a controlled environment.
A working proof of concept of the algorithm is shown. It has the potential of being a novel method of diagnosing and tracking arterial diseases. ...
While millions of people world wide suffer from arterial diseases, such as peripheral arterial disease, there are a limited number of methods that can be used to diagnose and track these diseases which are also easy, quick and non-invasive.
This work focuses on what is needed to improve diagnosing and tracking of peripheral arterial disease (PAD) using visualisation techniques. Visualising the blood flow pulsation in the skin can be useful in cases of arterial diseases, as the diseases can influence the blood flow by obstructions and arterial stiffness. The main objective in the visualisation is to show the acceleration of the blood flow, as this is linked to the arterial stiffness.
The proposed algorithm for visualising the acceleration of the blood flow is comprised of multiple steps, including techniques such as motion reduction, Eulerian video magnification, remote photoplethysmography signal extraction and using the second derivative. The input of this algorithm are videos of the skin of patients, this makes this method easy and non-invasive.
Photoplethysmography (PPG) signals are present in videos of skin, but can not be seen with the naked eye. Using Eulerian video magnification the PPG signals are amplified for better processing and visibility. By combining groups of pixels into small patches, a decrease in processing time is achieved and it adds a filtering effect. The size of the patches controls the resolution of the visualisation. Movement from the camera or patient is detrimental when extracting the PPG signal from the video. To counteract the motion in the videos a motion reduction step, using optical flow, is applied. Using the Plane-orthogonal-to-skin (POS) algorithm, the signal extracted from videos is converted to a PPG signal. Calculating the second derivative of the PPG signal gives the acceleration of the signal. By splitting the acceleration signal into positive and negative numbers, the acceleration and deceleration of the blood flow is visualised.
Synthetic videos simulating the skin were generated in various levels of accuracy to aid the development of the algorithm and to conduct experiments. The levels range from a simple pulsating square to a moving PPG signal over a blood vessel like structure. In addition, real videos of patients were used.
The experiments show the feasibility of visualising the acceleration of the blood flow pulsation in the skin, but also highlights areas of improvements and future research. More fine-tuning of the algorithm is needed, in addition to acquiring more videos of patients with PAD before and after surgery in a controlled environment.
A working proof of concept of the algorithm is shown. It has the potential of being a novel method of diagnosing and tracking arterial diseases.
This work focuses on what is needed to improve diagnosing and tracking of peripheral arterial disease (PAD) using visualisation techniques. Visualising the blood flow pulsation in the skin can be useful in cases of arterial diseases, as the diseases can influence the blood flow by obstructions and arterial stiffness. The main objective in the visualisation is to show the acceleration of the blood flow, as this is linked to the arterial stiffness.
The proposed algorithm for visualising the acceleration of the blood flow is comprised of multiple steps, including techniques such as motion reduction, Eulerian video magnification, remote photoplethysmography signal extraction and using the second derivative. The input of this algorithm are videos of the skin of patients, this makes this method easy and non-invasive.
Photoplethysmography (PPG) signals are present in videos of skin, but can not be seen with the naked eye. Using Eulerian video magnification the PPG signals are amplified for better processing and visibility. By combining groups of pixels into small patches, a decrease in processing time is achieved and it adds a filtering effect. The size of the patches controls the resolution of the visualisation. Movement from the camera or patient is detrimental when extracting the PPG signal from the video. To counteract the motion in the videos a motion reduction step, using optical flow, is applied. Using the Plane-orthogonal-to-skin (POS) algorithm, the signal extracted from videos is converted to a PPG signal. Calculating the second derivative of the PPG signal gives the acceleration of the signal. By splitting the acceleration signal into positive and negative numbers, the acceleration and deceleration of the blood flow is visualised.
Synthetic videos simulating the skin were generated in various levels of accuracy to aid the development of the algorithm and to conduct experiments. The levels range from a simple pulsating square to a moving PPG signal over a blood vessel like structure. In addition, real videos of patients were used.
The experiments show the feasibility of visualising the acceleration of the blood flow pulsation in the skin, but also highlights areas of improvements and future research. More fine-tuning of the algorithm is needed, in addition to acquiring more videos of patients with PAD before and after surgery in a controlled environment.
A working proof of concept of the algorithm is shown. It has the potential of being a novel method of diagnosing and tracking arterial diseases.
Bachelor thesis
(2017)
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Jelmer de Boer, Emilie de Bree, Pascal Remeijsen, Matthijs Verzijl, Koen Hindriks, Joost Broekens, Otto Visser, Huijuan Wang
A large problem that primary schools face is that the ratio of pupils to teachers is too high, the class sizes are too large and this makes it difficult for a single teacher to have a good oversight of how the development of a given child is going. The aim of Interactive Robotics is to tackle this problem by bringing robots into the classroom to aid teachers. They aim to have a single robot in a classroom that has the ability to teach different lessons and subjects; the RekenRobot being specifically for basic arithmetic. During the research phase, ideas were gathered regarding how to create teaching methods that are motivating and stimulating. For instance, personalisation, humanising the robot and adaptability of the teaching material were desired functions. The software for the RekenRobot was built from scratch, using the programming language GOAL, JavaScript, CSS, HTML and JSP. The original target audience of the project were children between the ages of 6 and 8. Later this was changed to cover different school years: 3-4, 5-6 and 7-8, making use of levels with different degrees of difficulty. The robot can work one-on-one with a child, being able to practice addition, subtraction, times tables and telling time, as well as 2 forms of explanations can be given: making use of a bus and a number line. Using no explanation to rather focus on automation is also an option. The idea of the project was to lay the groundwork for the later development of the RekenRobot, as this will be an ongoing project for Interactive Robotics. The application designed in this project will be adapted to become part of the Interactive Robotics system. The first user tests at primary schools yielded a largely positive result. The children were excited and motivated to work with the product. The system is simple enough to require very little explanation. This project was never meant to realise a product that can be deployed tomorrow, but the result is a very solid basis for further improvements.
...
A large problem that primary schools face is that the ratio of pupils to teachers is too high, the class sizes are too large and this makes it difficult for a single teacher to have a good oversight of how the development of a given child is going. The aim of Interactive Robotics is to tackle this problem by bringing robots into the classroom to aid teachers. They aim to have a single robot in a classroom that has the ability to teach different lessons and subjects; the RekenRobot being specifically for basic arithmetic. During the research phase, ideas were gathered regarding how to create teaching methods that are motivating and stimulating. For instance, personalisation, humanising the robot and adaptability of the teaching material were desired functions. The software for the RekenRobot was built from scratch, using the programming language GOAL, JavaScript, CSS, HTML and JSP. The original target audience of the project were children between the ages of 6 and 8. Later this was changed to cover different school years: 3-4, 5-6 and 7-8, making use of levels with different degrees of difficulty. The robot can work one-on-one with a child, being able to practice addition, subtraction, times tables and telling time, as well as 2 forms of explanations can be given: making use of a bus and a number line. Using no explanation to rather focus on automation is also an option. The idea of the project was to lay the groundwork for the later development of the RekenRobot, as this will be an ongoing project for Interactive Robotics. The application designed in this project will be adapted to become part of the Interactive Robotics system. The first user tests at primary schools yielded a largely positive result. The children were excited and motivated to work with the product. The system is simple enough to require very little explanation. This project was never meant to realise a product that can be deployed tomorrow, but the result is a very solid basis for further improvements.